Background: Low prescription rates of antipsychotic long-acting injections (LAIs) may be a major challenge in the prevention and treatment of schizophrenia. However, there are few studies on the usage and attitude toward LAIs among community-based patients with schizophrenia.Methods: A large community-based cross-sectional investigation was conducted among 6,336 patients with schizophrenia from Shanghai, China from March 1 to June 30, 2021. The structured Attitude and Status toward Treatment of Community Patients with Schizophrenia Questionnaire (AST-CSQ) was used to investigate the attitude and influencing factors of community-dwelling patients with schizophrenia toward LAIs.Results: Among the 6,336 participants, the average age was 49.28 ± 11.23. The rate of agreement to LAI antipsychotics among participants was 3.16% (n = 200). The family financial resources, care ability, and disease course of the LAIs group were less than those of the non-LAIs group. However, the LAIs group had higher immediate family guardianship, social activity, previous hospitalization, number of hospitalization, outpatient adherence, previous antipsychotic use, antipsychotic adherence, and attitude toward oral antipsychotics than the non-LAIs group, with significant differences between the two groups (p < 0.05). Furthermore, age (β = −0.036, OR 0.964, 95% CI 0.947–0.982), marital status (β = 0.237, OR 1.267, 95% CI 1.002–1.602), care ability (β = 0.709, OR 2.032, 95% CI 1.437–2.875), outpatient adherence (β = −0.674, OR 0.510, 95% CI 0.358–0.725), antipsychotic adherence (β = 0.920, OR 2.509, 95% CI 1.092–5.764), and attitude toward oral antipsychotics (β = −1.357, OR 0.258, 95% CI 0.103–0.646) were significant predictors of attitude toward LAI antipsychotics (p < 0.05).Conclusions: The community-dwelling patients with schizophrenia in China had a low willingness to use LAIs. Patients of a younger age, more hospitalizations, and a shorter course of disease were prone to be more willing to accept LAIs. The patients' age, marital status, care ability, outpatient adherence, antipsychotic adherence, and attitude toward oral antipsychotics were important predictor of patients' attitudes toward LAIs. Under the global deinstitutionalized management model of mental disorders, these results highlight an urgent problems for public mental health service providers and policy-makers and provide more solutions for them.

To identify clinical risk factors for diabetes mellitus (DM) in long-stay schizophrenia (LS-SCZ) patients, explore shared molecular mechanisms of schizophrenia and DM, and validate targeted interventions. Clinical data of LS-SCZ patients were analyzed via multiple logistic regression to identify DM risk factors. Differentially expressed genes (DEGs) from GSE53987/GSE161355 datasets were screened; overlapping DEGs were analyzed for co-expression and KEGG enrichment. Support vector machine (SVM) selected feature genes whose diagnostic efficacy was evaluated by ROC curves. Molecular docking verified Genistein’s binding with feature gene proteins. Risk factors for diabetes in LS-SCZ patients included age ≥50 years, hospitalization >20 years, BRI >5.306, family history of diabetes, and hypertension (all p < 0.05). Molecularly, 27 overlapping DEGs from two datasets were enriched in neuroactive ligand–receptor interaction, HIF-1, and MAPK pathways. SVM identified four feature genes (NPY, MKNK2, IFITM3, and S100A8) with good diagnostic efficacy. Genistein bound strongly to their proteins (binding energies: −8.98 to −6.026 kcal/mol). In conclusion, LS-SCZ patients have high DM risk. Targeting clinical risk factors and using Genistein for feature genes may reduce DM comorbidity.

Background: Patients with schizophrenia (SCZ) receiving antipsychotic treatment frequently develop metabolic complications, yet the mechanisms underlying liver-immune crosstalk remain poorly characterized. Methods: This study recruited 340 antipsychotic-treated SCZ patients and 340 matched healthy controls, with a 2-year follow-up restricted to the patient cohort. Candidate genes with hepatic metabolic relevance were screened from the independent GSE21138 brain transcriptomic dataset using machine learning. Molecular docking was performed to predict binding interactions of quercetin as a candidate bioactive compound. Results: Long-term antipsychotic exposure was associated with elevated serum 9-hydroxyrisperidone (9-OH-RISP) and substantial changes in liver function and metabolic markers; drug metabolite concentrations correlated with hepatic indices. Transcriptomic analysis identified 317 differentially expressed genes, from which 26 genes with liver-metabolism-related functions were selected as candidates. Seven hub genes (ABHD6, ALDH4A1, ETNPPL, etc.) were further identified via Support Vector Machine and Random Forest algorithms, and these genes were enriched in metabolic pathways, ferroptosis and other key signaling cascades. Unsupervised clustering based on hub gene expression stratified patients into high-inflammation (C2) and low-inflammation (C1) subtypes. The C2 subtype displayed computationally estimated enrichment of immune cells including B cells and naive CD8⁺ T cells. Molecular docking predicted strong binding affinity (binding energy ≤ −7.0 kcal/mol) between quercetin and proteins encoded by six hub genes, implying potential multi-target anti-inflammatory and metabolic–regulatory interactions. Conclusions: This study highlights the involvement of liver–immune crosstalk in antipsychotic-associated metabolic perturbations. The findings suggest exploratory potential for quercetin as a candidate bioactive compound in high-inflammatory SCZ subtypes, though these in silico predictions require further experimental validation.

Background: Mild cognitive impairment (MCI) is a critical early stage of Alzheimer’s disease (AD). Elucidating the comorbidity characteristics, influencing factors, and molecular mechanisms between MCI and AD in community-based populations is crucial for early intervention in cognitive impairment. Methods: 2,234 elderly individuals aged 50 years or older from 14 communities in Pudong New District, Shanghai, were enrolled in this study. The Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE), and Clinical Dementia Rating (CDR) were used to divide individuals into a control group ( n = 1,160) and an MCI group ( n = 1,074). The associations of demographic characteristics, lifestyle, and psychological status with MCI were analyzed. Transcriptome data from GSE140829 (training set) and GSE63060 (validation set) were obtained from the GEO database. Weighted gene co-expression network analysis (WGCNA) was used to identify MCI signature genes. KEGG pathway analysis was combined with the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway to elucidate mechanisms of comorbidity. Targeted intervention agents were screened based on the DSigDB database. Molecular docking (MD) was used to evaluate the binding ability between small molecules and target proteins. Results: The prevalence of AD in the MCI group (30.17%) was significantly higher than that in the control group ( p < 0.001), and MCI and AD were significantly positively correlated. Age, gender, smoking, living arrangements, mobile phone use, pet ownership, stress, anxiety, and depression were key influencing factors for MCI ( p < 0.05). The proportion of individuals living with children and grandchildren (57.45%) in the MCI group was significantly higher than that in the control group (16.29%) ( p < 0.001). WGCNA identified 273 MCI signature genes. KEGG pathway analysis showed that these genes were significantly enriched in neurodegenerative disease pathways, including AD pathways (with the AD pathway ranking first in the “Human Diseases” category). Targeted intervention screening identified the natural compounds boldine (comprehensive score 961.58) and piceatannol (comprehensive score 358.46) as potential drug candidates ( p < 0.05), both of which have strong binding ability to target proteins. Conclusion: MCI patients in the community are at high risk of AD, and their comorbidity characteristics are affected by multidimensional lifestyle and psychological factors. Boldine and piceatannol may be potential natural compounds for the intervention of cognitive impairment. The results of this study can provide a theoretical basis for the early prevention and precise intervention of cognitive impairment in the community.